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Comparative study of continuous hourly energy consumption forecasting strategies with small data sets to support demand management decisions in buildings
(2022)
Buildings are one of the largest consumers of electrical energy, making it important to develop different strategies to help to reduce electricity consumption. Building energy consumption forecasting strategies are widely ...
Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption
(ELSEVIER SCIENCE SA, 2008)
There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. ...
A data-driven forecasting strategy to predict continuous hourly energy demand in smart buildings
(2021)
Smart buildings seek to have a balance between energy consumption and occupant com-fort. To make this possible, smart buildings need to be able to foresee sudden changes in the build-ing’s energy consumption. With the help ...
FORECASTING OF PETROLEUM CONSUMPTION IN BRAZIL USING THE INTENSITY OF ENERGY TECHNIQUE
(Butterworth-heinemann LtdOxfordInglaterra, 1993)
Applied LSTM neural network time series to forecast household energy consumption
(SCOPUS, 2021-07)
In Ecuador, energy consumption is accentuated in
the residential sector due to population growth and other
parameters, which leads to an increase in energy costs,
greenhouse gas emissions and fossil fuel subsidies. ...
Analysis of the integration of drift detection methods in learning algorithms for electrical consumption forecasting in smart buildings
(2022)
Buildings are currently among the largest consumers of electrical energy with considerable increases in CO2 emissions in recent years. Although there have been notable advances in energy efficiency, buildings still have ...
Short-term forecasting of industrial electricity consumption in Brazil
(John Wiley & Sons LtdW SussexInglaterra, 1999)